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932 results for “CAP”
Aquarius CAP Level 3 Sea Surface Salinity Rain Corrected Standard Mapped Image 7-Day Data V5.0
Version 5.0 Aquarius CAP Level 3 products are the fourth release of the AQUARIUS/SAC-D mapped salinity and wind speed data based on the Combined Active Passive (CAP) algorithm. CAP Level 3 standard mapped image products contain gridded 1 degree spatial resolution salinity and wind speed data averaged over 7 day and monthly time scales. This particular dataset is the 7-Day running mean sea surface salinity (SSS) rain corrected V5.0 Aquarius CAP product. CAP is a P.I. produced dataset developed and provided by JPL. The CAP algorithm utilizes data from both the onboard radiometer and scatterometer to simultaneously retrieve salinity, wind speed and direction by minimizing the sum of squared differences between model and observations. The main improvements in CAP V5.0 relative to the previous version include: updates to the Geophysical Model Functions to 4th order harmonics with the inclusion of sea surface temperature (SST) and stability at air-sea interface effects; use of the Canadian Meteorological Center (CMC) SST product as the new source ancillary sea surface temperature data in place of NOAA OI SST. The Aquarius instrument is onboard the AQUARIUS/SAC-D satellite, a collaborative effort between NASA and the Argentinian Space Agency Comision Nacional de Actividades Espaciales (CONAE). The instrument consists of three radiometers in push broom alignment at incidence angles of 29, 38, and 46 degrees incidence angles relative to the shadow side of the orbit. Footprints for the beams are: 76 km (along-track) x 94 km (cross-track), 84 km x 120 km and 96km x 156 km, yielding a total cross-track swath of 370 km. The radiometers measure brightness temperature at 1.413 GHz in their respective horizontal and vertical polarizations (TH and TV). A scatterometer operating at 1.26 GHz measures ocean backscatter in each footprint that is used for surface roughness corrections in the estimation of salinity. The scatterometer has an approximate 390km swath.
Aquarius CAP Level 3 Sea Surface Salinity Rain Corrected Standard Mapped Image Monthly Data V5.0
Version 5.0 Aquarius CAP Level 3 products are the fourth release of the AQUARIUS/SAC-D mapped salinity and wind speed data based on the Combined Active Passive (CAP) algorithm. CAP Level 3 standard mapped image products contain gridded 1 degree spatial resolution salinity and wind speed data averaged over 7 day and monthly time scales. This particular dataset is the monthly sea surface salinity (SSS) rain corrected V5.0 Aquarius CAP product. CAP is a P.I. produced dataset developed and provided by JPL. The CAP algorithm utilizes data from both the onboard radiometer and scatterometer to simultaneously retrieve salinity, wind speed and direction by minimizing the sum of squared differences between model and observations. The main improvements in CAP V5.0 relative to the previous version include: updates to the Geophysical Model Functions to 4th order harmonics with the inclusion of sea surface temperature (SST) and stability at air-sea interface effects; use of the Canadian Meteorological Center (CMC) SST product as the new source ancillary sea surface temperature data in place of NOAA OI SST. The Aquarius instrument is onboard the AQUARIUS/SAC-D satellite, a collaborative effort between NASA and the Argentinian Space Agency Comision Nacional de Actividades Espaciales (CONAE). The instrument consists of three radiometers in push broom alignment at incidence angles of 29, 38, and 46 degrees incidence angles relative to the shadow side of the orbit. Footprints for the beams are: 76 km (along-track) x 94 km (cross-track), 84 km x 120 km and 96km x 156 km, yielding a total cross-track swath of 370 km. The radiometers measure brightness temperature at 1.413 GHz in their respective horizontal and vertical polarizations (TH and TV). A scatterometer operating at 1.26 GHz measures ocean backscatter in each footprint that is used for surface roughness corrections in the estimation of salinity. The scatterometer has an approximate 390km swath.
Aquarius CAP Level 3 Wind Speed Standard Mapped Image 7-Day Data V5.0
Version 5.0 Aquarius CAP Level 3 products are the fourth release of the AQUARIUS/SAC-D mapped salinity and wind speed data based on the Combined Active Passive (CAP) algorithm. CAP Level 3 standard mapped image products contain gridded 1 degree spatial resolution salinity and wind speed data averaged over 7 day and monthly time scales. This particular dataset is the 7-Day running mean wind speed V5.0 Aquarius CAP product. CAP is a P.I. produced dataset developed and provided by JPL. The CAP algorithm utilizes data from both the onboard radiometer and scatterometer to simultaneously retrieve salinity, wind speed and direction by minimizing the sum of squared differences between model and observations. The main improvements in CAP V5.0 relative to the previous version include: updates to the Geophysical Model Functions to 4th order harmonics with the inclusion of sea surface temperature (SST) and stability at air-sea interface effects; use of the Canadian Meteorological Center (CMC) SST product as the new source ancillary sea surface temperature data in place of NOAA OI SST. The Aquarius instrument is onboard the AQUARIUS/SAC-D satellite, a collaborative effort between NASA and the Argentinian Space Agency Comision Nacional de Actividades Espaciales (CONAE). The instrument consists of three radiometers in push broom alignment at incidence angles of 29, 38, and 46 degrees incidence angles relative to the shadow side of the orbit. Footprints for the beams are: 76 km (along-track) x 94 km (cross-track), 84 km x 120 km and 96km x 156 km, yielding a total cross-track swath of 370 km. The radiometers measure brightness temperature at 1.413 GHz in their respective horizontal and vertical polarizations (TH and TV). A scatterometer operating at 1.26 GHz measures ocean backscatter in each footprint that is used for surface roughness corrections in the estimation of salinity. The scatterometer has an approximate 390km swath.
ECCO Geometry Parameters for the Lat-Lon-Cap 90 (llc90) Native Model Grid (Version 4 Release 4)
This dataset provides geometric parameters for the lat-lon-cap 90 (llc90) native model grid from the ECCO Version 4 Release 4 (V4r4) ocean and sea-ice state estimate. Parameters include areas and lengths of grid cell sides; horizontal and vertical coordinates of grid cell centers and corners; grid rotation angles; and global domain geometry including bathymetry and land/ocean masks. Estimating the Circulation and Climate of the Ocean (ECCO) state estimates are dynamically and kinematically-consistent reconstructions of the three-dimensional, time-evolving ocean, sea-ice, and surface atmospheric states. ECCO V4r4 is a free-running solution of a global, nominally 1-degree configuration of the MIT general circulation model (MITgcm) that has been fit to observations in a least-squares sense. Observational data constraints used in V4r4 include sea surface height (SSH) from satellite altimeters [ERS-1/2, TOPEX/Poseidon, GFO, ENVISAT, Jason-1,2,3, CryoSat-2, and SARAL/AltiKa]; sea surface temperature (SST) from satellite radiometers [AVHRR], sea surface salinity (SSS) from the Aquarius satellite radiometer/scatterometer, ocean bottom pressure (OBP) from the GRACE satellite gravimeter; sea ice concentration from satellite radiometers [SSM/I and SSMIS], and in-situ ocean temperature and salinity measured with conductivity-temperature-depth (CTD) sensors and expendable bathythermographs (XBTs) from several programs [e.g., WOCE, GO-SHIP, Argo, and others] and platforms [e.g., research vessels, gliders, moorings, ice-tethered profilers, and instrumented pinnipeds]. V4r4 covers the period 1992-01-01T12:00:00 to 2018-01-01T00:00:00.
Aquarius CAP Level 3 Sea Surface Salinity Standard Mapped Image 7-Day Data V5.0
Version 5.0 Aquarius CAP Level 3 products are the fourth release of the AQUARIUS/SAC-D mapped salinity and wind speed data based on the Combined Active Passive (CAP) algorithm. Level 3 standard mapped image products contain gridded 1 degree spatial resolution salinity and wind speed data averaged over 7 day and monthly time scales. This particular dataset is the 7-Day running mean sea surface salinity (SSS) V5.0 Aquarius CAP product. CAP is a P.I. produced dataset developed and provided by JPL. The CAP algorithm utilizes data from both the onboard radiometer and scatterometer to simultaneously retrieve salinity, wind speed and direction by minimizing the sum of squared differences between model and observations. The main improvements in CAP V5.0 relative to the previous version include: updates to the Geophysical Model Functions to 4th order harmonics with the inclusion of sea surface temperature (SST) and stability at air-sea interface effects; use of the Canadian Meteorological Center (CMC) SST product as the new source ancillary sea surface temperature data in place of NOAA OI SST. The Aquarius instrument is onboard the AQUARIUS/SAC-D satellite, a collaborative effort between NASA and the Argentinian Space Agency Comision Nacional de Actividades Espaciales (CONAE). The instrument consists of three radiometers in push broom alignment at incidence angles of 29, 38, and 46 degrees incidence angles relative to the shadow side of the orbit. Footprints for the beams are: 76 km (along-track) x 94 km (cross-track), 84 km x 120 km and 96km x 156 km, yielding a total cross-track swath of 370 km. The radiometers measure brightness temperature at 1.413 GHz in their respective horizontal and vertical polarizations (TH and TV). A scatterometer operating at 1.26 GHz measures ocean backscatter in each footprint that is used for surface roughness corrections in the estimation of salinity. The scatterometer has an approximate 390km swath.
Aquarius CAP Level 3 Sea Surface Salinity Standard Mapped Image Monthly Data V5.0
Version 5.0 Aquarius CAP Level 3 products are the fourth release of the AQUARIUS/SAC-D mapped salinity and wind speed data based on the Combined Active Passive (CAP) algorithm. CAP Level 3 standard mapped image products contain gridded 1 degree spatial resolution salinity and wind speed data averaged over 7 day and monthly time scales. This particular dataset is the monthly sea surface salinity (SSS) V5.0 Aquarius CAP product. CAP is a P.I. produced dataset developed and provided by JPL. The CAP algorithm utilizes data from both the onboard radiometer and scatterometer to simultaneously retrieve salinity, wind speed and direction by minimizing the sum of squared differences between model and observations. The main improvements in CAP V5.0 relative to the previous version include: updates to the Geophysical Model Functions to 4th order harmonics with the inclusion of sea surface temperature (SST) and stability at air-sea interface effects; use of the Canadian Meteorological Center (CMC) SST product as the new source ancillary sea surface temperature data in place of NOAA OI SST. The Aquarius instrument is onboard the AQUARIUS/SAC-D satellite, a collaborative effort between NASA and the Argentinian Space Agency Comision Nacional de Actividades Espaciales (CONAE). The instrument consists of three radiometers in push broom alignment at incidence angles of 29, 38, and 46 degrees incidence angles relative to the shadow side of the orbit. Footprints for the beams are: 76 km (along-track) x 94 km (cross-track), 84 km x 120 km and 96km x 156 km, yielding a total cross-track swath of 370 km. The radiometers measure brightness temperature at 1.413 GHz in their respective horizontal and vertical polarizations (TH and TV). A scatterometer operating at 1.26 GHz measures ocean backscatter in each footprint that is used for surface roughness corrections in the estimation of salinity. The scatterometer has an approximate 390km swath.
Figure 1 from: Costa MC, Medolago CAB, Murcia A, Francisco MR (2020) Reproductive parameters of the Chestnut-capped Blackbird, Chrysomus ruficapilus (Passeriformes: Icteridae), in a natural wetland from southeastern Brazil. Zoologia 37: 1-5. https://doi.org/10.3897/zoologia.37.e36026
Figure 1 Nesting site of Chrysomus ruficapillus. Study area with high density of Rhynchospora corymbosa (L.), emergent plant preferentially used for nest building. Photo: MC Costa.
Figure 3-6 from: Costa MC, Medolago CAB, Murcia A, Francisco MR (2020) Reproductive parameters of the Chestnut-capped Blackbird, Chrysomus ruficapilus (Passeriformes: Icteridae), in a natural wetland from southeastern Brazil. Zoologia 37: 1-5. https://doi.org/10.3897/zoologia.37.e36026
Figure 3-6 Nests, eggs and nestling of Chrysomus ruficapillus. (3) Side view of a nest. (4) Details of the nest and egg. (5) Details of a newly born nestling and two eggs. (6) Details of two nestlings with 6-7 days. Photos: MC Costa and CAB Medolago.
Figure 2 from: Costa MC, Medolago CAB, Murcia A, Francisco MR (2020) Reproductive parameters of the Chestnut-capped Blackbird, Chrysomus ruficapilus (Passeriformes: Icteridae), in a natural wetland from southeastern Brazil. Zoologia 37: 1-5. https://doi.org/10.3897/zoologia.37.e36026
Figure 2 Numbers of active nests (incubation and nestling stages) of Chrysomus ruficapilus for the reproductive season of 2017/2018.
Docking Adenosine Receptor Ligands to SARS-CoV2 mRNA Cap 2'-O-Methyltransferase: Energy Minimized Structures
<p>Energy minimized structures associated with a study docking adenosine receptor binders and related ligands to the adenosine binding site on SARS-CoV2 nsp16. The associated paper is under review, but we have a previous version of the paper available as a preprint at <a href="https://chemrxiv.org/articles/preprint/Docking_Adenosine_Receptor_Ligands_to_SARS-CoV2_mRNA_Cap_Guanine-N7_Methyltransferase/12462080/2">https://chemrxiv.org/articles/preprint/Docking_Adenosine_Receptor_Ligands_to_SARS-CoV2_mRNA_Cap_Guanine-N7_Methyltransferase/12462080/2</a>.</p>
Figure 4 from: Toledo CAP, Castro Souza V, Lucas EJ (2020) Nomenclatural and taxonomic updates in Rourea subgen. Rourea sect. Multifoliolatae (Connaraceae). PhytoKeys 169: 137-175. https://doi.org/10.3897/phytokeys.169.54297
Figure 4 Rourea chrysomalla: A flowering branchlet B fruiting branchlet (photo by Jair Faria) C leaves (photo by Jair Faria) D habit.
Figure 11 from: Toledo CAP, Castro Souza V, Lucas EJ (2020) Nomenclatural and taxonomic updates in Rourea subgen. Rourea sect. Multifoliolatae (Connaraceae). PhytoKeys 169: 137-175. https://doi.org/10.3897/phytokeys.169.54297
Figure 11 Geographic distribution of Rourea macrocalyx (circles), R. prostrata (triangles) and R. tenuis (squares).
Figure 10 from: Toledo CAP, Castro Souza V, Lucas EJ (2020) Nomenclatural and taxonomic updates in Rourea subgen. Rourea sect. Multifoliolatae (Connaraceae). PhytoKeys 169: 137-175. https://doi.org/10.3897/phytokeys.169.54297
Figure 10 Rourea glazioui: A fruiting branchlet B leaf, adaxial surface C inflorescence (photo by Thiago Flores) D leaf, abaxial surface.
Figure 1 from: Toledo CAP, Castro Souza V, Lucas EJ (2020) Nomenclatural and taxonomic updates in Rourea subgen. Rourea sect. Multifoliolatae (Connaraceae). PhytoKeys 169: 137-175. https://doi.org/10.3897/phytokeys.169.54297
Figure 1 Leaves in Rourea subgen. R. sect. Multifoliolatae: AR. discolorBR. martianaCR. tenuisDR. cnestidifolia.
Figure 2 from: Toledo CAP, Castro Souza V, Lucas EJ (2020) Nomenclatural and taxonomic updates in Rourea subgen. Rourea sect. Multifoliolatae (Connaraceae). PhytoKeys 169: 137-175. https://doi.org/10.3897/phytokeys.169.54297
Figure 2 Rourea bahiensis: A flowering branchlet B habit C congested leaves D fruit E fruiting branchlet.
Figure 7 from: Toledo CAP, Castro Souza V, Lucas EJ (2020) Nomenclatural and taxonomic updates in Rourea subgen. Rourea sect. Multifoliolatae (Connaraceae). PhytoKeys 169: 137-175. https://doi.org/10.3897/phytokeys.169.54297
Figure 7 Rourea diamantina: A flowering branchlet B leaf, abaxial surface C indumentum, leaflet abaxial surface D flower, external view E flower, internal view F stamens G ovary, external view H ovary, internal view and ovules I fruit and seed, external view J seed, external view K sepal indumentum, external view.
Figure 3 from: Toledo CAP, Castro Souza V, Lucas EJ (2020) Nomenclatural and taxonomic updates in Rourea subgen. Rourea sect. Multifoliolatae (Connaraceae). PhytoKeys 169: 137-175. https://doi.org/10.3897/phytokeys.169.54297
Figure 3 Geographic distribution of Rourea bahiensis (circles), R. barbata (triangles) and R. blanchetiana (squares).
Data from: The genome of blue-capped cordon-bleu uncovers hidden diversity of LTR retrotransposons in zebra finch
Avian genomes have perplexed researchers by being conservative in both size and rearrangements, while simultaneously holding the blueprints for a massive species radiation during the last 65 My. Transposable elements (TEs) in bird genomes are relatively scarce but have been implicated as important hotspots for chromosomal inversions. In zebra finch (Taeniopygia guttata), long terminal repeat (LTR) retrotransposons have proliferated and are positively associated with chromosomal breakpoint regions. Here, we present the genome, karyotype and transposons of blue-capped cordon-bleu (Uraeginthus cyanocephalus), an African songbird that diverged from zebra finch at the root of estrildid finches 10 Mya. This constitutes the third linked-read sequenced genome assembly and fourth in-depth curated TE library of any bird. Exploration of TE diversity on this brief evolutionary timescale constitutes a considerable increase in resolution for avian TE biology and allowed us to uncover 4.5 Mb more LTR retrotransposons in the zebra finch genome. In blue-capped cordon-bleu, we likewise observed a recent LTR accumulation indicating that this is a shared feature of Estrildidae. Curiously, we discovered 25 new endogenous retrovirus-like LTR retrotransposon families of which at least 21 are present in zebra finch but were previously undiscovered. This highlights the importance of studying close relatives of model organisms.
Data from: Nest survival in year-round breeding tropical Red-capped Larks (Calandrella cinerea) increases with higher nest abundance but decreases with higher invertebrate availability and rainfall
Nest survival is critical to breeding in birds and plays an important role in life-history evolution and population dynamics. Studies evaluating the proximate factors involved in explaining nest survival and the resulting temporal patterns are biased in favor of temperate regions. Yet, such studies are especially pertinent to the tropics, where nest predation rates are typically high and environmental conditions often allow for year-round breeding. To tease apart the effects of calendar month and year, population-level breeding activity and environmental conditions, we studied nest survival over a 64-month period in equatorial, year-round breeding red-capped larks Calandrella cinerea in Kenya. We show that daily nest survival rates varied with time, but not in a predictable seasonal fashion among months or consistently among years. We found negative influences of flying invertebrate biomass and rain on nest survival and higher survival of nests when nests were more abundant, which suggests that nest predation resulted from incidental predation. Although an increase in nest predation is often attributed to an increase in nest predators, we suggest that in our study, it may be caused by altered predator activity resulting from increased activity of the primary prey, invertebrates, rather than activity of the red-capped larks. Our results emphasize the need to conduct more studies in Afro-tropical regions because proximate mechanisms explaining nest predation can be different in the unpredictable and highly variable environments of the tropics compared with the relatively predictable seasonal changes found in temperate regions. Such studies will aid in better understanding of the environmental influences on life-history variation and population dynamics in birds.
FIGURE 7 in The feather mites (Acari, Astigmata) of the Violet-capped Woodnymph, Thalurania glaucopis (Gmelin) (Aves, Trochilidae), with descriptions of three new species
FIGURE 7. Trochilodectes brevipenis sp. n. male: dorsal (A) and ventral (B) views.
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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OpenNeuro
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